ABSTRACT The program objective is to train predoctoral and postdoctoral biostatisticians in statistical theory and methods and collaboration as applied to environmental health sciences (EHS). The grant is administered through the Department of Biostatistics and Computational Biology (DBCB), in collaboration with the Departments of Environmental Medicine and Public Health Sciences. The eleven trainers are faculty in these departments, seven of whom are from DBCB. Training: The DBCB offers a PhD degree in Statistics, with a Bioinformatics and Computational Biology option, providing rigorous and state-of-the art statistical training. All pre- and postdoctoral trainees work on applied EHS projects under joint mentorship of a DBCB and an EHS trainer. These projects include the Seychelles Child Development Study, which examines neurodevelopmental effects of prenatal exposure to mercury and nutrients from fish consumption, and studies of the reproductive effects of phthalates, perfluoroalkyl substances, bisphenol A, and maternal stress. Involvement in these studies provides trainees with both statistical and EHS training, gives experience in reproducible research and communication, and often motivates trainees' methodologic research. Further EHS training is obtained through courses in epidemiology and toxicology, as well as lab tours and seminars customized to the trainees. Postdoctoral trainees enroll in DBCB and EHS courses appropriate to their experience and interest, work on EHS projects, and participate in all T32-related activities. All trainees present their work at local and national conferences. Program oversight is provided via monthly meetings of the T32 Executive Committee and annual evaluations by the External Advisory Board, and makes use of trainee evaluations to improve the program. Trainee selection: Emphasis is placed on recruiting trainees from diverse backgrounds and increasing representation of under-represented groups in the biostatistics profession. Successful applicants to the Statistics PhD program in DBCB will have completed a baccalaureate degree with a major in mathematics or statistics, or in science with a strong minor in mathematics or statistics. Predoctoral trainees for this training program are selected from among the Statistics PhD students, generally begin T32 support after two years of in the PhD program, and are appointed for up to four years. Postdoctoral trainees must have completed a PhD in statistics, mathematics, epidemiology or a related discipline, or have basic science training with strong quantitative skills, and are supported for up to three years. The program supports three predoctoral and one postdoctoral trainee.